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The Interplay Between Host Genetics and the Gut Microbiome Reveals Common bioRxiv preprint doi: https://doi.org/10.1101/2019.12.26.888313; this version posted January 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 1 The interplay between host genetics and the gut microbiome reveals common 2 and distinct microbiome features for human complex diseases 3 Fengzhe Xu1#, Yuanqing Fu1#, Ting-yu Sun2, Zengliang Jiang1,3, Zelei Miao1, Menglei 4 Shuai1, Wanglong Gou1, Chu-wen Ling2, Jian Yang4,5, Jun Wang6*, Yu-ming Chen2*, 5 Ju-Sheng Zheng1,3,7* 6 #These authors contributed equally to the work 7 1 School of Life Sciences, Westlake University, Hangzhou, China. 8 2 Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department 9 of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 10 China. 11 3 Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 12 Hangzhou, China. 13 4 Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 14 Australia. 15 5 Institute for Advanced Research, Wenzhou Medical University, Wenzhou, Zhejiang 16 325027, China 17 6 CAS Key Laboratory for Pathogenic Microbiology and Immunology, Institute of 18 Microbiology, Chinese Academy of Sciences, Beijing, China. 19 7 MRC Epidemiology Unit, University of Cambridge, Cambridge, UK. 20 21 Short title: Interplay between and host genetics and gut microbiome 22 1 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.26.888313; this version posted January 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 2 23 *Correspondence to 24 Prof Ju-Sheng Zheng 25 School of Life Sciences, Westlake University,18 Shilongshan Rd, Cloud Town, 26 Hangzhou, China. Tel: +86 (0)57186915303. Email: [email protected] 27 And 28 Prof Yu-Ming Chen 29 Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of 30 Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China. 31 Email: [email protected] 32 And 33 Prof Jun Wang 34 CAS Key Laboratory for Pathogenic Microbiology and Immunology, Institute of 35 Microbiology, Chinese Academy of Sciences, Beijing, China. 36 Email: [email protected] 37 2 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.26.888313; this version posted January 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 3 38 Abstract 39 There is increasing interest about the interplay between host genetics and gut 40 microbiome on human complex diseases, with prior evidence mainly derived from 41 animal models. In addition, the shared and distinct microbiome features among 42 human complex diseases remain largely unclear. We performed a microbiome 43 genome-wide association study to identify host genetic variants associated with gut 44 microbiome in a Chinese population with 1475 participants. We then conducted 45 bi-directional Mendelian randomization analyses to examine the potential causal 46 associations between gut microbiome and human complex diseases. We found that 47 Saccharibacteria (also known as TM7 phylum) could potentially improve renal 48 function by affecting renal function biomarkers (i.e., creatinine and estimated 49 glomerular filtration rate). In contrast, atrial fibrillation, chronic kidney disease and 50 prostate cancer, as predicted by the host genetics, had potential causal effect on gut 51 microbiome. Further disease-microbiome feature analysis suggested that gut 52 microbiome features revealed novel relationship among human complex diseases. 53 These results suggest that different human complex diseases share common and 54 distinct gut microbiome features, which may help re-shape our understanding about 55 the disease etiology in humans. 56 3 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.26.888313; this version posted January 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 4 57 Introduction 58 Ever-increasing evidence has suggested that gut microbiome is involved in many 59 physiological processes, such as energy harvest, immune response, and neurological 60 function1-3. With successes of investigation into the clinical application of fecal 61 transplants, modulation of gut microbiome has emerged as a potential treatment 62 option for some complex diseases, including inflammatory bowel disease and 63 colorectal cancer 4,5. However, it is still unclear whether the gut microbiome has the 64 potential to be clinically applied for the prevention or treatment of many other 65 complex diseases. Therefore, it is important to clarify the bi-directional causal 66 association between gut microbiome and human complex diseases or traits. 67 68 Mendelian randomization (MR) is a method that uses genetic variants as instrumental 69 variables to investigate the causality between an exposure and outcome in 70 observational studies6. Prior literature provides evidence that the composition or 71 structure of the gut microbiome can be influenced by the host genetics7-10. On the 72 other hand, host genetic variants associated with gut microbiome were rarely explored 73 in Asian populations, thus we are still lacking instrument variables to perform MR for 74 gut microbiome in Asians. This calls for novel microbiome genome-wide association 75 study (GWAS) in Asian populations. 76 77 Along with the causality issue between the gut microbiome and human complex 78 diseases, it is so far unclear whether human complex diseases had similar or unique 4 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.26.888313; this version posted January 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 5 79 gut microbiome features. Identifying common and distinct gut microbiome features 80 across different diseases might shed light on novel relationships among the complex 81 diseases and update our understanding about the disease etiology in humans. However, 82 the composition and structure of gut microbiome are influenced by a variety of factors 83 including environment, diet and regional variation 11-13, which posed a key challenge 84 for the description of representative microbiome features for a specific disease. 85 Although there were several studies comparing disease-related gut microbiome 14-16, 86 few of them has examined and compared the microbiome features across different 87 human complex diseases. 88 89 In the present study, we performed a microbiome GWAS in a Chinese cohort study: 90 the Guangzhou Nutrition and Health Study (GNHS)17, including 1475 participants. 91 Subsequently, we applied a bi-directional MR method to explore the genetically 92 predicted relationship between gut microbiome and human complex diseases. To 93 explore novel relationships among human complex diseases based on gut microbiome, 94 we investigated the shared and distinct gut microbiome features across diverse human 95 complex diseases 18. 96 97 Result 98 Overview of the study 99 Our study was based on the GNHS, with 4048 participants (40-75 years old) living in 100 urban Guangzhou city recruited during 2008 and 2013 17. In the GNHS, stool samples 5 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.26.888313; this version posted January 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 6 101 were collected among 1937 participants during follow-up visits, among which 1475 102 unrelated participants without taking anti-biotics were included in our discovery 103 microbiome GWAS. We then included additional 199 participants with both genetic 104 and gut microbiome data as a replication cohort, which belonged to the control arm of 105 a case-control study of hip fracture in Guangdong Province, China 19. 106 107 For both discovery and replication cohorts, genotyping was carried out with Illumina 108 ASA-750K arrays. Quality control and relatedness filters were performed by 109 PLINK1.9 20. We conducted the genome-wide genotype imputation with 1000 110 Genomes Phase3 v5 reference panel by Minimac321-23. HLA region was imputed with 111 Pan-Asian reference panel and SNP2HLA v1.0.3 24-26. 112 113 Association of host genetics with gut microbiome features 114 We performed a series of microbiome GWAS with PLINK 1.9 based on logistic 115 models for binary variables 20. For continuous variables, we used GCTA with mixed 116 linear model-based association (MLMA) method 27,28. We also analyzed categorical 117 variable enterotypes of the participants based on genus-level relative abundance of gut 118 microbiome, using the Jensen-Shannon Distance (JSD) and the Partitioning Around 119 Medoids (PAM) clustering algorithm 29. The participants were subsequently clustered 120 into two groups according to the enterotypes (Prevotella vs Bacteroides). Thereafter, 121 we performed GWAS for enterotypes using logistic regression model to explore 122 potential associations between host genetics and enterotypes. However, we did not 6 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.26.888313; this version posted January 6, 2020.
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